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Showing 1 to 15 of 32 results Save | Export
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Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
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Oslington, Gabrielle; Mulligan, Joanne; Van Bergen, Penny – Educational Studies in Mathematics, 2020
This paper describes elementary students' awareness and representation of the aggregate properties and variability of data sets when engaged in predictive reasoning. In a design study, 46 third-graders interpreted a table of historical temperature data to predict and represent future monthly maximum temperatures. The task enabled students to…
Descriptors: Grade 3, Elementary School Students, Logical Thinking, Thinking Skills
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Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
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Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
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Hourigan, Mairéad; Leavy, Aisling – Teaching Statistics: An International Journal for Teachers, 2016
As part of Japanese Lesson study research focusing on "comparing and describing likelihoods", fifth grade elementary students used real-world data in decision-making. Sporting statistics facilitated opportunities for informal inference, where data were used to make and justify predictions.
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Statistics
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Hung, Jui-Long; Shelton, Brett E.; Yang, Juan; Du, Xu – IEEE Transactions on Learning Technologies, 2019
Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…
Descriptors: Prediction, Models, At Risk Students, Identification
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Bush, Sarah B.; Albanese, Judith; Karp, Karen S. – Mathematics Teaching in the Middle School, 2016
Historically, some baby names have been more popular during a specific time span, whereas other names are considered timeless. The Internet article, "How to Tell Someone's Age When All You Know Is Her Name" (Silver and McCann 2014), describes the phenomenon of the rise and fall of name popularity, which served as a catalyst for the…
Descriptors: Mathematics Instruction, Grade 6, Prediction, Data Collection
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Brinkhuis, Matthieu J. S.; Savi, Alexander O.; Hofman, Abe D.; Coomans, Frederik; van der Maas, Han L. J.; Maris, Gunter – Journal of Learning Analytics, 2018
With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion…
Descriptors: Data Analysis, Mathematics Instruction, Accuracy, Reaction Time
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Ng, Kelvin H. R.; Hartman, Kevin; Liu, Kai; Khong, Andy W. H. – International Educational Data Mining Society, 2016
During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/division. The learning environment first modeled and then supported the use of a scripted series…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Arithmetic, Problem Solving
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Fick, Sarah J.; Songer, Nancy Butler – Journal of Education in Science, Environment and Health, 2017
Recent reforms emphasize a shift in how students should learn and demonstrate knowledge of science. These reforms call for students to learn content knowledge using science and engineering practices, creating integrated science knowledge. While there is existing literature about the development of integrated science knowledge assessments, few…
Descriptors: Climate, Middle School Students, Integrated Activities, Scientific Literacy
Bonsu, Pam; Goertzen, Heidi; Howard-Brown, Beth; Kaase, Kris; LaTurner, Jason; Times, Chris – Southeast Comprehensive Center, 2016
The Southeast Comprehensive Center (SECC) at SEDL, an affiliate of American Institutes for Research (AIR), partnered with the Alabama State Department of Education (ALSDE) in 2014 to assist in evaluating Alabama Plan 2020, mainly focusing on learners and the graduation rate. SECC provided professional development and analytic technical assistance…
Descriptors: Data Analysis, Graduation Rate, Strategic Planning, Faculty Development
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Khajah, Mohammad; Lindsey, Robert V.; Mozer, Michael C. – International Educational Data Mining Society, 2016
In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better.…
Descriptors: Bayesian Statistics, Data Analysis, Prediction, Intelligent Tutoring Systems
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Rice, Kerry; Hung, Jui-Long – International Journal of Technology in Teaching and Learning, 2015
This case study explored the potential applications of data mining in the educational program evaluation of online professional development workshops for pre K-12 teachers. Multiple data mining analyses were implemented in combination with traditional evaluation instruments and student outcomes to determine learner engagement and more clearly…
Descriptors: Case Studies, Online Courses, Program Evaluation, Faculty Development
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Mong, Michael D.; Mong, Kristi W. – Journal of Behavioral Education, 2012
The present study evaluated the utility of brief experimental analysis (BEA) in predicting effective interventions for increasing the math fluency of 3 elementary students identified as having math skill deficits. Baseline data were collected followed by implementation of a BEA consisting of the following interventions: cover, copy, and compare,…
Descriptors: Intervention, Instructional Effectiveness, Prediction, Experiments
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Jocson, Rosanne M.; Alampay, Liane Pena; Lansford, Jennifer E. – International Journal of Behavioral Development, 2012
The relations of education, authoritarian child-rearing attitudes, and endorsement of corporal punishment to Filipino parents' reported use of corporal punishment were examined using two waves of data. Structured interviews using self-report questionnaires were conducted with 117 mothers and 98 fathers from 120 families when their children were 8…
Descriptors: Higher Education, Mothers, Child Rearing, Interviews
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